BACKGROUND: Within the given environment of scarce health care resources and increasing demands on the health care system, it is imperative to organise health care in the most efficient manner. Sustainability of the overall system, equity issues concerning access to care and a move to patient-centred care - informing the decision making process by patient needs, are current hot topics when considering care, from curative through to the end of life.
The decision making process within UK’s health care sector is relying on a standardised approach including the benefits and the costs of interventions and "guarantees" that resources are used in a way, which provide best value. This approach falls short when looking at interventions at the end of life, jeopardising appropriate focus and attention for end of life and palliative care.
AIM: The aim of the thesis is threefold:
1. Understanding the current landscape of ’resource use data collection’ and deriving costs at the end of life in an UK setting.
2. Reflect on the challenges, benefits and limitations of using administrative data versus trial data in an end of life care setting.
3. Present potential solutions to challenges arising in collecting and analysing cost of end of life care and recommendations for further research.
METHODS: This work starts by highlighting why end of life care is an outlier when considering the measurement and allocation of health care resources. An update of a systematic review is then presented to identify current methodology used to capture resource use and cost assignment at the end of life. The benefits and limitations of using administrative data or clinical trial data to capture these components is then explored via a series of case studies. The administrative data studies are retrospective whole population secondary care administrative data linkage studies, capturing resources used in the last year prior to death.
The first clinical trial is a two-arm parallel group cluster randomised (1:1) trial on pain assessment, the second, a feasibility trial of an Exercise and Nutrition-based Rehabilitation program at the end of life.
RESULTS: Most of the results from the included studies are in line with the results of the systematic review. There is a wide variety of perspectives, approaches to resource use collection, costing sources and derivation of costs making a comparison between studies challenging.
As the administrative data studies included whole population data, they provided novel insight into the main drivers of secondary care resource use in patients last year of life namely the cause of death being, despite age being a confounding factor, of greater importance than age itself. Further, some equity issues, related to rurality were proven, which was shown to be of bigger influence than deprivation. Different illnesses require various levels of care intensity and are therefore connected to specific care pathways, with cancer care showing an exceptionally high need for secondary care involvement. Both of the studies showed a massive increase in secondary care use with proximity to death, especially within the last three month.
The two clinical trials included, showcase different approaches of increasing patients quality of life whilst keeping the impact on resource use low. Both of the trials confirmed secondary care use as the main driver of costs. The second, despite being a small scale feasibility trial, showing a considerable share of resource use falling outside secondary care, hence demonstrate the need to include multiple data sources when aiming to understand the “true cost” of end of life care.
Data collection and costing within administrative data studies and clinical trials comes with specific benefits and limitations, some of which could potentially be addressed when combining data generated through trials with administrative data.
CONCLUSION: Fair evidence based decision-making requires comprehensive knowledge of the current state of the system, being conscious of the costs and the benefits of interventions and having a system in place which enables comparing different interventions, which in itself requires a standardised way to capture costs and benefits.
This thesis presents various examples of different approaches to resource use collection and applying costs. In order to be able to recommend at least a Scotland wide costing strategy for costing administrative datasets, more research is needed to understand the impact of different costing methods applied to the same dataset.
Within clinical trials, collection of resource use data should be kept to a minimum in order to keep patient burden low. The development of a standardized questionnaire is recommended, highlighting the need for adaptability to different trials.
Linkage between data collected from individual trials and administrative data is an appealing concept, offering extensive data whilst keeping the patient burden at a minimum. Looking at the current landscape of data protection regulations, there are yet some hurdles to overcome
